Libraries
library(rvest)
## Loading required package: xml2
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(plotly)
## Loading required package: ggplot2
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
library(readr)
##
## Attaching package: 'readr'
## The following object is masked from 'package:rvest':
##
## guess_encoding
讀取資料
states = read_csv("Seasons_Stats.csv")
## Parsed with column specification:
## cols(
## .default = col_integer(),
## Player = col_character(),
## Pos = col_character(),
## Tm = col_character(),
## PER = col_double(),
## TSp = col_double(),
## FTr = col_double(),
## OWS = col_double(),
## DWS = col_double(),
## WS = col_double(),
## `WS/48` = col_double(),
## `FG%` = col_double(),
## TwoPp = col_double(),
## `eFG%` = col_double(),
## `FT%` = col_double()
## )
## See spec(...) for full column specifications.
TS%
tsp_by_year = states %>% group_by(Year) %>% summarise(mean=mean(TSp, na.rm=TRUE))
plot_ly(tsp_by_year, x= tsp_by_year$Year ,y= tsp_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))
## Warning: Ignoring 1 observations
2分球命中率變化
TwoPp_by_year = states %>% group_by(Year) %>% summarise(mean=mean(TwoPp, na.rm=TRUE))
plot_ly(TwoPp_by_year, x= TwoPp_by_year$Year ,y= TwoPp_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))
## Warning: Ignoring 1 observations
3分球命中率變化
ThreePp_by_year = states %>% group_by(Year) %>% summarise(mean=mean(ThreePp, na.rm=TRUE))
plot_ly(ThreePp_by_year, x= TwoPp_by_year$Year ,y= ThreePp_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))
## Warning: Ignoring 31 observations
罰球出手數變化
FTA_by_year = states %>% group_by(Year) %>% summarise(mean=mean(FTA, na.rm=TRUE))
plot_ly(FTA_by_year, x= FTA_by_year$Year ,y= FTA_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))
## Warning: Ignoring 1 observations